Using MATLAB for Data Analysis

Organize and Explore Data

Organize your data with datatypes designed for tabular, time-series, categorical, and text data. Use the MATLAB language to write programs based on thousands of algorithms from a wide variety of domains. Interactively customize visualizations, then automatically generate the MATLAB code to reproduce them with new data.

Analyze Data with Less Code

MATLAB apps allow you to interactively perform iterative tasks such as training machine learning models or labeling data. These apps then generate the MATLAB code needed to programmatically reproduce the work you did interactively.

Use a prebuilt family of functions for identifying and cleaning sensor drift, signal outliers, missing data, and noise. Combine separate data sets by joining tables and synchronizing time-series data. Live Editor Tasks let you interactively solve these problems within your live script and generate the code for you. Learn how to use new MATLAB functions with extensive and professionally written documentation.

Expand Your Analysis with Few Changes

Use parfor loops and multiprocessor hardware to accelerate parallel analysis with almost no code changes. Create gpuarrays to take advantage of GPU acceleration for appropriate algorithms. Process out-of-memory data sets using tall arrays, which overload hundreds of functions throughout the data analysis workflow to operate on out-of-memory data.